Abstract

This article is concerned with the effects of piecewise constant argument on exponential stability to a unique equilibrium state of bidirectional associative memories (BAMs) neural networks model. Based on the fixed point theorem approach and an integral inequality of Gronwall type with deviation arguments, we have derived sufficient criteria to guarantee the existence, uniqueness and global exponential stability of the equilibrium state for the BAM model. Finally, the efficiency of the theoretical results has been illustrated by providing two numerical examples with simulations.